pygmt.clib.Session.virtualfile_from_grid¶

Session.virtualfile_from_grid(grid)[source]¶

Store a grid in a virtual file.

Use the virtual file name to pass in the data in your grid to a GMT module. Grids must be xarray.DataArray instances.

Context manager (use in a with block). Yields the virtual file name that you can pass as an argument to a GMT module call. Closes the virtual file upon exit of the with block.

The virtual file will contain the grid as a GMT_MATRIX with extra metadata.

Use this instead of creating a data container and virtual file by hand with create_data, put_matrix, and open_virtual_file

The grid data matrix must be C contiguous in memory. If it is not (e.g., it is a slice of a larger array), the array will be copied to make sure it is.

Parameters: grid (xarray.DataArray) – The grid that will be included in the virtual file.
Yields: fname (str) – The name of virtual file. Pass this as a file name argument to a GMT module.

Examples

>>> from pygmt.datasets import load_earth_relief
>>> from pygmt.helpers import GMTTempFile
>>> data = load_earth_relief(resolution='60m')
>>> print(data.shape)
(181, 361)
>>> print(data.lon.values.min(), data.lon.values.max())
-180.0 180.0
>>> print(data.lat.values.min(), data.lat.values.max())
-90.0 90.0
>>> print(data.values.min(), data.values.max())
-8592.145 5558.7925
>>> with Session() as ses:
...     with ses.virtualfile_from_grid(data) as fin:
...         # Send the output to a file so that we can read it
...         with GMTTempFile() as fout:
...             args = '{} -L0 -Cn ->{}'.format(fin, fout.name)
...             ses.call_module('grdinfo', args)
...             print(fout.read().strip())
-180 180 -90 90 -8592.14453125 5558.79248047 1 1 361 181
>>> # The output is: w e s n z0 z1 dx dy n_columns n_rows